import requests
import datetime
import pandas as pd
import pymysql
from sklearn.preprocessing import MinMaxScaler
from joblib import dump

class WeatherUtils(oject):
    """天气类
       object(_type_):_description_
    """

    def __init__(self):
        self.date_list = [
            '2024-07-01',
            '2024-08-01',
            '2024-09-01',
            '2024-10-01',
            '2024-11-01',
            '2024-12-01',
        ]
        self.url = 'http://v1.yiketianqi.com/api'

    def get_data(self):
        """获取天气数据
        """
        data_list = []
        for d in self.date_list:
            conf = {
                'appid':'88249599',#使用自己注册的appid
                'appsecret':'BA7zIjrM',
                'version':'history',
                'year':d[:4],
                'month':d[5:7],
                'city':'南昌'
            }

            #发啊送请求获取数据
            res = requests.get(self.url + '?',params=conf)
            res_data = res.json()
            #print(res_data)
            #break
            for i in res_data['data']:
                data_list.append({
                    'data':datetime.datetime.strptime(i['ymd'],'%Y-%m-%d'),
                    'bWendu':i['bWendu'],
                    'yWendu':i['yWendu'],
                    'tianqi':i['tianqi'],
                    'fengli':i['fengil'],
                })
        df = pd.DataFrame(data_list)
        df.to_csv('./timing/weather.csv')

class MysqlUtils(object):

    def __init__(self) -> None:
        self.conn = pymysql.connect(
            host='127.0.0.1',
            user='root',
            password='root',
            database='scenic',
            port='3306',
            charset='utf8mb4'
        )
        self.weather_data = pd.read_csv('./timing/weather.csv')

def is_holiday(self, date):
    """
    是否节假日判断
    """
    if date in ['2024-09-03', '2024-10-01', '2024-10-02', '2024-10-03', '2024-10-04', '2024-10-05', '2024-10-06', '2024-10-07', '2025-01-01', '2025-01-02','2025-01-03']:
         return 1
    return 0

def get_data(self):
    cursor = self.conn.cursor(cursor=pymysql.cursors.DictCursor)
    sql = """
    SELECT DATE(g.create_time) as date, count(*) as count FROM order_user_gate_rel g WHERE DATE(G.create_time) < '2025-01-01' GROUP BY date
"""
    cursor.execute(sql)
    ret = cursor.fetchall()
    df = pd.DataFrame(ret)

    #合并天气数据
    self.weather_data['date'] = pd.to_datetime(self.weather_data['date'])
    df['date'] = pd.to_datetime(df['date'])
    df_pivot = pd.merge(self.weather_data,df,on='date')
    print(df_pivot.head)
    df_pivot.set_index('date',inplace=True)
    
    df_pivot['dow'] = df_pivot.index.dayofweek #星期几（0-6）
    df_pivot['month'] = df_pivot.index.month #月份
    df_pivot['is_holiday'] = df_pivot.index.map(self.is_holiday)
    ##print(df_pivot.head)

    ##对星期几和月份进行独热编码
    df_pivot = pd.get_dummies(df_pivot, columns=['dow', 'month','tianqi','fengli'], dtype=int)
    #对温度进行类型转换
    df_pivot['bWendu'] = df_pivot['bWendu'].str.replace('°','').astype(int)
    df_pivot['yWendu'] = df_pivot['yWendu'].str.replace('°','').astype(int)

    ##归一化入园数
    scaler = MinMaxScaler()
    features = df_pivot[['count']]
    sdf_pivot[['count']] = scaler.fit_transform(features)
    #归一化天气
    weather_features = df_pivot[['bWendu'.'yWendu']]
    dump(scaler,'timiing/scaler.joblib')
    df_pivot[['bWendu'.'yWendu']] = scaler.fit_transform(weather_features)
    dump(weather_features,/timing/weather_features.joblib)
    df_pivot.to_csv('timing/scenic_data.csv', index=False)

if __name__ == '__main__':
    #wu = WeatherUtils()
    #wu.get_data()
    mu = MysqlUtils()
    mu.get_data()
